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Mindel, V.

Publications and source records attributed to Mindel, V..

7 recordsLinked to original sources

Activator-binding domains are required but insufficient for Med15 recruitment to UAS, revealing a critical role for its disordered C-terminus in directing genome targeting

The Mediator complex is a conserved transcriptional coactivator that bridges transcription factors (TFs) with the core transcriptional machinery. In budding yeast, TFs recruit the Mediator to upstream activation sequences (UASs) by interacting with three activator-binding domains (ABDs) within the Med15 tail subunit. However, these ABD-TF interactions exhibit relatively low affinity, raising the question of whether they fully account for Med15 recruitment in vivo. Here, we address this question by combining genome-wide profiling with systematic mutational analysis. We demonstrate that while the three ABDs are collectively required for Med15 recruitment, they are not individually required and are not sufficient to specify the genomic binding pattern of Med15. Instead, removal of an intrinsically disordered C-terminal redistributes Med15 occupancy across UASs. Notably, C-terminal truncation alters Med15 binding even at TF-depleted regions, and these effects are recapitulated by deleting Med2 or Med3, which further stabilize TF-dependent recruitment. Together, these findings support a dual mechanism of Med15 UAS recruitment, whereby TF-ABD recruitment is directed and stabilized by C-terminal mediated interactions.

genomics↗

Beyond motif recognition: Specificity of human transcription factors in yeast

Transcription factors (TFs) bind DNA through sequence-specific DNA-binding domains (DBDs), yet genome-wide analyses show that TFs occupy only a small fraction of their motif occurrences. This raises the question of how TFs distinguish specific targets from the many potential sites in the genome. To investigate determinants of binding specificity beyond the cognate motif and cofactor influences, we measured the binding of 60 human TFs across the budding yeast genome. Although human TFs robustly recognized their motifs, they displayed strong selectivity in site occupancy. Nucleosome abundance explained this selectivity only in part: among the 5-20% of motif sites that were bound, a substantial fraction remained nucleosome covered. Furthermore, TFs recognizing similar motif sequences independently localized to distinct subsets of sites within different promoters. Despite the absence of human-specific cofactors in yeast, both binding stability and genomic preferences depended on largely disordered non-DBD regions. These findings suggest intrinsically disordered regions (IDRs) may therefore direct genome binding TF target recognition across evolutionarily distant genomes. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=124 SRC="FIGDIR/small/721015v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@7db4cborg.highwire.dtl.DTLVardef@e88903org.highwire.dtl.DTLVardef@7b3e11org.highwire.dtl.DTLVardef@127ef29_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

Asymmetric crosstalk between the BMP and TGFβ pathways resolves signaling ambiguity

The BMP and TGF{beta} signaling pathways control cellular fate decisions in diverse biological contexts, often playing opposing roles. Despite extensive knowledge of these pathways, understanding how cells respond to environments containing these opposing cues remains a challenge. Here, we systematically analyze the activation of these pathways under combinatorial signaling environments. We find that TGF{beta} ligands inhibit BMP signaling, while BMP ligands enhance TGF{beta} transcriptional response across concentrations, ligand variants, and cell types. This asymmetric crosstalk results in the activation of a TGF{beta}-biased transcriptional response, even under mixed signaling conditions, effectively reducing signal ambiguity, with implications for processes such as EMT. We show that this crosstalk originates downstream of the SMAD proteins phosphorylation. Using mathematical models, we predict, and experimentally verify, that promiscuous interactions between SMAD proteins provide the mechanism for the observed crosstalk. Our findings challenge the canonical models, suggesting an active role for mediator proteins in determining biological responses.

systems biology↗

On the overlap of transcription factor binding and regulatory targets: functional and regulatory coherence of top-bound targets is masked by weakly bound ones

A recent study that systematically mapped genomic bindings and regulatory effects of transcription factors (TFs) reported a surprisingly low overlap between TF binding and regulatory targets in Saccharomyces cerevisiae1. Our analysis suggests that this conclusion depends on the permissive definition of binding targets, which includes a large fraction of weakly bound sites.

genomics↗

Protein massively parallel binding assay reveals transcription factor binding determinants

Transcription factors select their genomic binding sites in genomes depending on their DNA binding domain (DBD) but also on regions outside the DBD (nonDBD). However, it remains challenging to define these determinants within nonDBDs and reveal their mechanism of action. Towards this, we introduce here an in-vivo method for parallel analysis of thousands of designed peptides for binding a DNA sequence of interest (Protein Massively Parallel Binding Assay, pMPBA). We apply it to scan the full sequence space of budding yeast TFs and generate a detailed map of DNA localizing determinants. Within the set of predicted DBDs, we reveal a large variation in DNA binding affinities, depending on the family and on different sequence characteristics, including charge. Strong signals were not confined to predicted DBDs but included a considerable fraction of nonDBD peptides, most of which were predicted as intrinsically disordered. pMPBA opens new possibilities for high-throughput analysis of peptide-DNA binding within cells.

genomics↗

Massively Parallel Binding Assay (MPBA) reveals limited transcription factor binding cooperativity, challenging models of specificity

DNA binding domains (DBDs) within transcription factors (TFs) recognize short sequence motifs that are highly abundant in genomes. In vivo, TFs bind only a small subset of motif occurrences, which is often attributed to the cooperative binding of interacting TFs at proximal motifs. However, large-scale testing of this model is still lacking. Here, we describe a novel method allowing parallel measurement of TF binding to thousands of designed sequences within yeast cells and apply it to quantify the binding of dozens of TFs to libraries of regulatory regions containing clusters of binding motifs, systematically mutating all motif combinations. With few exceptions, TF occupancies were well explained by independent binding to individual motifs, with motif cooperation being of only limited effects. Our results challenge the general role of motif combinatorics in directing TF genomic binding and open new avenues for exploring the basis of protein-DNA interactions within cells.

systems biology↗

Stable and functionally diverse versatile peroxidases by computational design directly from sequence

White-rot fungi secrete a repertoire of high-redox potential oxidoreductases to efficiently decompose lignin. Of these enzymes, versatile peroxidases (VPs) are the most promiscuous biocatalysts. VPs are attractive enzymes for research and industrial use, but their recombinant production is extremely challenging. To date, only a single VP has been structurally characterized and optimized for recombinant functional expression, stability and activity. Computational enzyme optimization methods can be applied to many enzymes in parallel, but they require accurate structures. Here, we demonstrate that model structures computed by deep-learning based ab initio structure prediction methods are reliable starting points for one-shot PROSS stability-design calculations. Four designed VPs encoding as many as 43 mutations relative to the wild type enzymes are functionally expressed in yeast whereas their wild type parents are not. Three of these designs exhibit substantial and useful diversity in reactivity profile and tolerance to environmental conditions. The reliability of the new generation of structure predictors and design methods increases the scale and scope of computational enzyme optimization, enabling efficient discovery and exploitation of the functional diversity in natural enzyme families.

biochemistry↗